Development and validation of a prediction model for long-term sickness absence based on occupational health survey variables

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Development and validation of a prediction model for long-term sickness absence based on occupational health survey variables. / Roelen, Corné; Thorsen, Sannie; Heymans, Martijn; Twisk, Jos; Bültmann, Ute; Bjørner, Jakob.

In: Disability and Rehabilitation, Vol. 40, No. 2, 2018, p. 168-175.

Research output: Contribution to journalJournal articleResearchpeer-review

Harvard

Roelen, C, Thorsen, S, Heymans, M, Twisk, J, Bültmann, U & Bjørner, J 2018, 'Development and validation of a prediction model for long-term sickness absence based on occupational health survey variables', Disability and Rehabilitation, vol. 40, no. 2, pp. 168-175. https://doi.org/10.1080/09638288.2016.1247471

APA

Roelen, C., Thorsen, S., Heymans, M., Twisk, J., Bültmann, U., & Bjørner, J. (2018). Development and validation of a prediction model for long-term sickness absence based on occupational health survey variables. Disability and Rehabilitation, 40(2), 168-175. https://doi.org/10.1080/09638288.2016.1247471

Vancouver

Roelen C, Thorsen S, Heymans M, Twisk J, Bültmann U, Bjørner J. Development and validation of a prediction model for long-term sickness absence based on occupational health survey variables. Disability and Rehabilitation. 2018;40(2):168-175. https://doi.org/10.1080/09638288.2016.1247471

Author

Roelen, Corné ; Thorsen, Sannie ; Heymans, Martijn ; Twisk, Jos ; Bültmann, Ute ; Bjørner, Jakob. / Development and validation of a prediction model for long-term sickness absence based on occupational health survey variables. In: Disability and Rehabilitation. 2018 ; Vol. 40, No. 2. pp. 168-175.

Bibtex

@article{96d533796b524541af11a7ca2f650fa2,
title = "Development and validation of a prediction model for long-term sickness absence based on occupational health survey variables",
abstract = "Purpose: The purpose of this study is to develop and validate a prediction model for identifying employees at increased risk of long-term sickness absence (LTSA), by using variables commonly measured in occupational health surveys.Materials and methods: Based on the literature, 15 predictor variables were retrieved from the DAnish National working Environment Survey (DANES) and included in a model predicting incident LTSA (≥4 consecutive weeks) during 1-year follow-up in a sample of 4000 DANES participants. The 15-predictor model was reduced by backward stepwise statistical techniques and then validated in a sample of 2524 DANES participants, not included in the development sample. Identification of employees at increased LTSA risk was investigated by receiver operating characteristic (ROC) analysis; the area-under-the-ROC-curve (AUC) reflected discrimination between employees with and without LTSA during follow-up.Results: The 15-predictor model was reduced to a 9-predictor model including age, gender, education, self-rated health, mental health, prior LTSA, work ability, emotional job demands, and recognition by the management. Discrimination by the 9-predictor model was significant (AUC = 0.68; 95{\%} CI 0.61–0.76), but not practically useful.Conclusions: A prediction model based on occupational health survey variables identified employees with an increased LTSA risk, but should be further developed into a practically useful tool to predict the risk of LTSA in the general working population.Implications for rehabilitationLong-term sickness absence risk predictions would enable healthcare providers to refer high-risk employees to rehabilitation programs aimed at preventing or reducing work disability.A prediction model based on health survey variables discriminates between employees at high and low risk of long-term sickness absence, but discrimination was not practically useful.Health survey variables provide insufficient information to determine long-term sickness absence risk profiles.There is a need for new variables, based on the knowledge and experience of rehabilitation professionals, to improve long-term sickness absence risk profiles.",
author = "Corn{\'e} Roelen and Sannie Thorsen and Martijn Heymans and Jos Twisk and Ute B{\"u}ltmann and Jakob Bj{\o}rner",
year = "2018",
doi = "10.1080/09638288.2016.1247471",
language = "English",
volume = "40",
pages = "168--175",
journal = "Disability and Rehabilitation",
issn = "0963-8288",
publisher = "Taylor & Francis",
number = "2",

}

RIS

TY - JOUR

T1 - Development and validation of a prediction model for long-term sickness absence based on occupational health survey variables

AU - Roelen, Corné

AU - Thorsen, Sannie

AU - Heymans, Martijn

AU - Twisk, Jos

AU - Bültmann, Ute

AU - Bjørner, Jakob

PY - 2018

Y1 - 2018

N2 - Purpose: The purpose of this study is to develop and validate a prediction model for identifying employees at increased risk of long-term sickness absence (LTSA), by using variables commonly measured in occupational health surveys.Materials and methods: Based on the literature, 15 predictor variables were retrieved from the DAnish National working Environment Survey (DANES) and included in a model predicting incident LTSA (≥4 consecutive weeks) during 1-year follow-up in a sample of 4000 DANES participants. The 15-predictor model was reduced by backward stepwise statistical techniques and then validated in a sample of 2524 DANES participants, not included in the development sample. Identification of employees at increased LTSA risk was investigated by receiver operating characteristic (ROC) analysis; the area-under-the-ROC-curve (AUC) reflected discrimination between employees with and without LTSA during follow-up.Results: The 15-predictor model was reduced to a 9-predictor model including age, gender, education, self-rated health, mental health, prior LTSA, work ability, emotional job demands, and recognition by the management. Discrimination by the 9-predictor model was significant (AUC = 0.68; 95% CI 0.61–0.76), but not practically useful.Conclusions: A prediction model based on occupational health survey variables identified employees with an increased LTSA risk, but should be further developed into a practically useful tool to predict the risk of LTSA in the general working population.Implications for rehabilitationLong-term sickness absence risk predictions would enable healthcare providers to refer high-risk employees to rehabilitation programs aimed at preventing or reducing work disability.A prediction model based on health survey variables discriminates between employees at high and low risk of long-term sickness absence, but discrimination was not practically useful.Health survey variables provide insufficient information to determine long-term sickness absence risk profiles.There is a need for new variables, based on the knowledge and experience of rehabilitation professionals, to improve long-term sickness absence risk profiles.

AB - Purpose: The purpose of this study is to develop and validate a prediction model for identifying employees at increased risk of long-term sickness absence (LTSA), by using variables commonly measured in occupational health surveys.Materials and methods: Based on the literature, 15 predictor variables were retrieved from the DAnish National working Environment Survey (DANES) and included in a model predicting incident LTSA (≥4 consecutive weeks) during 1-year follow-up in a sample of 4000 DANES participants. The 15-predictor model was reduced by backward stepwise statistical techniques and then validated in a sample of 2524 DANES participants, not included in the development sample. Identification of employees at increased LTSA risk was investigated by receiver operating characteristic (ROC) analysis; the area-under-the-ROC-curve (AUC) reflected discrimination between employees with and without LTSA during follow-up.Results: The 15-predictor model was reduced to a 9-predictor model including age, gender, education, self-rated health, mental health, prior LTSA, work ability, emotional job demands, and recognition by the management. Discrimination by the 9-predictor model was significant (AUC = 0.68; 95% CI 0.61–0.76), but not practically useful.Conclusions: A prediction model based on occupational health survey variables identified employees with an increased LTSA risk, but should be further developed into a practically useful tool to predict the risk of LTSA in the general working population.Implications for rehabilitationLong-term sickness absence risk predictions would enable healthcare providers to refer high-risk employees to rehabilitation programs aimed at preventing or reducing work disability.A prediction model based on health survey variables discriminates between employees at high and low risk of long-term sickness absence, but discrimination was not practically useful.Health survey variables provide insufficient information to determine long-term sickness absence risk profiles.There is a need for new variables, based on the knowledge and experience of rehabilitation professionals, to improve long-term sickness absence risk profiles.

U2 - 10.1080/09638288.2016.1247471

DO - 10.1080/09638288.2016.1247471

M3 - Journal article

VL - 40

SP - 168

EP - 175

JO - Disability and Rehabilitation

JF - Disability and Rehabilitation

SN - 0963-8288

IS - 2

ER -

ID: 169282159